Methods and systems for neural architecture search

Abstract

Methods and systems are provided for neural architecture search. In a system with suitable processing circuitry, a preferred model may be determined for performing a selected task, with the determining including obtaining a computational graph that includes a plurality of nodes and a corresponding plurality of weightings configured to scale input data into the nodes. The computational graph defines a first model and a second model with each of the models including a subgraph in the computational graph, with one or more of the plurality of weightings being shared between the first model and the second model. One or more weightings of each of the models may be updated based on training of each of the models to perform the selected task, and the preferred model may be identified based on an analysis of both models. A neural network for performing the selected task may be configured based on the preferred model.